Spinning Enterprise Data into Revenues with Analytics

Nov 4, 2015

Jay Larson

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Analytics

Data

Enterprise

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It was Rumpelstiltskin who had an amazing alchemic device – a spinning wheel – that turned straw into gold. Since then, many companies have attempted to replicate this type of magical transformation, with limited success. But, in all seriousness, business-savvy CIOs are now using enterprise analytics to monetize the vast stores of data generated every day through customer interactions and the businesses itself.

As I blogged about earlier this week, revenues pave the path to CIOs’ growing influence in the C-suite. This post gets into the details of how a custom-built analytics product can help CIOs to generate revenues, and how easy it can be to build that analytics product.

Monetizing enterprise data

Let’s look at a wireless communications company in Asia, for example. Every day, through the course of business, it collects an abundance of data on customer activity, including which ads customers looked at, as well as data on geolocation and mobile tagging. (This kind of data may not be collected or available for release, in an anonymized format, in certain countries.)

The telecommunications company started selling the data, scrubbed of any personal identifying information (PII), to advertisers several years ago. The data was sold in a raw format, and advertisers were free to structure and analyze it in any way they saw fit.

However, as its data business grew, the wireless company realized that advertisers were asking a fairly consistent set of questions such as:

“I want to understand an audience of 18-to-24 year olds. What are the top mobile ads they respond to in XYZ shopping mall?”

“What is the best location within ABC neighborhood to place bus shelter advertising with a scannable QR code? Which shelter had the highest scan rate over a specific two-week period?”

By developing its own analytics application, the wireless company can now enable its customers to rapidly answer these questions, instead of trying to extract answers from raw data. In this way, the wireless company vastly increased the ultimate value of its enterprise data – advertisers were willing to pay four times as much for analytic informationcompared to the raw anonymized data.

Now, the wireless company is generating revenue as an analytics and insights company, owning both the data and the discovery platform. Not surprisingly, custom research has turned into a significant moneymaker for the wireless company.

Building engagement with analytics

Analytics are also a great way to engage customers with your brand. Stronger engagement is proven to yield more revenues from existing customers, and analytics enable them to become intimately familiar with how they use your product or service.

For example, an electric utility in California provides energy consumption analytics for customers on its web site and mobile app. Research has proven that customers who use these analytics to monitor their energy usage have bills that are 5% to 20% lower than those who don’t. Equally important, the state’s Public Utilities Commission financially rewards the energy company when consumption drops – a net revenue stream.

These are just a couple of examples of how CIOs can use analytics to turn enterprise data into revenues. There are opportunities in literally every industry, from healthcare to consumer packaged goods.